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[trackingdata] scores returns None, if no detections in range

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This commit is contained in:
Jan Grewe 2025-02-24 11:45:24 +01:00
parent d300f72949
commit 35be41282a
1 changed files with 4 additions and 2 deletions
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fixtracks/utils/trackingdata.py
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@ -169,11 +169,11 @@ class TrackingData(QObject):
numpy.ndarray numpy.ndarray
A NumPy array of type float32 containing the keypoint scores of the shape (N, M) A NumPy array of type float32 containing the keypoint scores of the shape (N, M)
with N the number of detections and M the number of keypoints. with N the number of detections and M the number of keypoints.
""" """
if selection: if selection:
if len(self._indices) < 1: if len(self._indices) < 1:
logging.info("TrackingData.scores returns empty array, not detections in range!") logging.info("TrackingData.scores returns empty array, not detections in range!")
return np.ndarray([]) return None
return np.stack(self._data["keypoint_score"][self._indices]).astype(np.float32) return np.stack(self._data["keypoint_score"][self._indices]).astype(np.float32)
return np.stack(self._data["keypoint_score"]).astype(np.float32) return np.stack(self._data["keypoint_score"]).astype(np.float32)
@ -195,6 +195,8 @@ class TrackingData(QObject):
A NumPy array of shape (N, 2) containing the center of gravity for each detection. A NumPy array of shape (N, 2) containing the center of gravity for each detection.
""" """
scores = self.keypointScores(selection) scores = self.keypointScores(selection)
if scores is None:
return None
scores[scores < threshold] = 0.0 scores[scores < threshold] = 0.0
scores[:, np.setdiff1d(np.arange(scores.shape[1]), nodes)] = 0.0 scores[:, np.setdiff1d(np.arange(scores.shape[1]), nodes)] = 0.0
weighted_coords = self.coordinates(selection=selection) * scores[:, :, np.newaxis] weighted_coords = self.coordinates(selection=selection) * scores[:, :, np.newaxis]